model based analysis of the indian electricity …...indian energy system, along with the economical...

15. Symposium Energieinnovation, 14.-16.02.2018, Graz/Austria

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MODEL BASED ANALYSIS OF THE INDIAN ELECTRICITY

ECONOMICS

Karthik Subramanya BHAT1*, Gerald FEICHTINGER2, Udo BACHHIESL3, Heinz

STIGLER4

Institut für Elektrizitätswirtschaft und Energieinnovation, Technische Universität Graz

Abstract:

India is a country with a huge electricity system having a transmission network

spanning over more than 145,400 circuit kilometres (1), 330 GW of installed power

plant capacity (2), and 900 TWh of annual electricity consumption (3). In between an

energy transition process towards carbon free energy, India has to successfully

manage the transition while maintaining its rapidly increasing economic growth. India’s

agreement to the COP 21 Paris treaty to reduce its carbon intensity of energy

generation has shown its intent towards battling the adverse effects of climate change,

on a global level. Additionally, the lessons that were learned from the unchecked

expansion of cheap coal power plant capacity resulting from the economic reforms of

1990 (4), puts the Indian policy makers on their toes with respect to the present ‘Make

in India’ industrial initiative. The Indian electricity sector faces several problems already

and would face even more challenges when considering such a drastic change in its

system.

For a sustainable and successful transition, the country has to strategize its energy

transition to such an extent that it not only solves the already prevailing problems of

electricity access, security of supply, and exponentially increasing demand, but also

prevents the financial failure of the country’s energy sector. Thus, a model-based

analysis is an absolute requirement, if we are to strategize the energy transition on

such a level. Interestingly, the model developed for this study is one of the first of its

kind, considering both the physical and the economic structures and limitations of the

Indian electricity sector. Using such a techno-economic model, studies can be

conducted with several scenarios for a target year of say 2050, to check the

sustainability of its energy strategies and if necessary, to provide the best possible

alternatives. The development, analysis and the possible results of such a techno

economic simulation model is thoroughly discussed in the scope of this study.

Keywords: India, Electricity Transition, Renewable Energies, Model-based analysis

1 Institut für Elektrizitätswirtschaft und Energieinnovation, Technische Universität Graz, [email protected]




mailto:[email protected]





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1 Introduction:

India in today’s global energy scenario is known for its large market potential for

energy transition, as the country is heavily dependent on conventional sources like

coal and oil for satisfying its energy needs. Moreover, the country’s economy is

booming in the last few years of intensive globalization, and since its economy is

closely related with the manufacturing industry, a strong coupling of the country’s

economic development and its primary energy use has been forcefully established.

This creates a situation where an energy transition in the country creates an adverse

effect on the manufacturing sector and thus in turn the economic development.

Therefore, a sustainable solution is gravely needed to ensure the energy transition in

the country without any adverse effects on the country’s economic development. This

calls for a careful and detailed long-term planning of the energy assets in the country

in the coming future. A detailed analysis of the electricity sector can only performed by

a model-based analysis of both the technical and the economic situation of the

country’s energy sector. Additionally, electricity consumption forms a major part of the

primary energy consumption of the country. The electricity sector in India is also heavily

dependent on coal and gas-based technologies for electricity generation, so a

transition in the electricity sector would be an optimum starting point for the complete

energy transition in the country. Since 2003, the Indian electricity market has also

gradually in the ongoing process of complete liberalization, bringing it closer to the

market situation in the European Union and several other ‘developed’ countries.

As mentioned before, a detailed analysis of both the technical and the economic

situation of the electricity sector in India is also necessary for predicting the future

development paths and to calculate several significant indicators for each development

path as evaluation. In this study, such a model-based approach has been proposed for

the Indian electricity economics, and an attempt has been made to look into several

possible futures for the development of the Indian electricity sector.

2 Electricity transition for India:

Electricity has already become the back bone of economy in the world. Similarly, in

India, electricity became significantly important to the country during the industrial and

economic reforms periods beginning from 1990. Several power plants were

continuously added without the necessary planning, to cope up with the rapid

industrialization caused due to the economic reforms. The manufacturing sector of

India started growing at a rapid pace, increasing the base demand for electricity in the

country also at a rapid rate as a result.

The standard of living in the country started improving along with economic

development. The number of electric appliances in each household increased at a

steady pace. On the other hand, the population of India has also been steadily

increasing, creating a requirement for creating more households, resulting in


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urbanization and thus adding to the increasing demand growth considerably. Poorly

maintained transmission networks and distribution networks also inversely affected the

prevailing problem of demand and supply gap caused due to deficiency of generating

capacities to support the massive population and the industries.

2.1 Dependency of the Indian power sector on coal power

India’s electrical transformation requires a bigger push than most of the other electrical

economies, due to its unique dependency on its coal fired power plant fleet. After the

economic reforms of 1990, India put major priority on the manufacturing sector spurring

the economy to improve, thereby creating a large industrial demand. This led to the

unchecked continuous addition of coal fired capacities. For a long time now, the Indian

electricity system prioritizes base load coverage, which covers up to 52% of the yearly

peak. A figure (1) shows the illustration of the base load in India.

Figure (1) base load situation in India

To sustain the economic development, the manufacturing sector grew larger every

year, and without a sustainable strategy, the coal power plant fleet also started to grow

at an unimaginable pace. Initially, most of the coal used in the power sector was cheap

coal mined internally, but eventually, as the coal fired power plant technology started

improving, India started observing a large import in the high grade overseas coal. With

time, an unbreakable dependency of the Indian economy on coal imports was

established.

Once India agreed to the Paris agreement to curtail the energy related emissions by

30 percent till the year 2030, the importance of the dependency on coal power was

identified as a challenge by many experts. With subsequent addition of variable

renewable energy capacities like solar PV and wind power, India needed the coal

power plants to stabilize the electricity generation. To lose the dependency on coal, a

good strategy involving the use of several other possible technology shares has to be

planned. This is only possible with a simulation model capable of simulating the

electricity system both technically and economically. In the scope of this study, such a

simulation model has been used to analyse the Indian electricity economics.


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3 The Indian Power sector:

A figure (2) clearly describes the situation of the Indian Power Sector, by providing an

overview over the installed electricity generation capacity by technology types (3). As

it can be observed, out of 330 GW of installed capacity, around 60 percent of the

installed capacity is coal fired, producing around 75 percent share of the overall annual

electricity generated. However, there has been a considerable increase in the share of

the renewable energy capacity in the last few years, majorly comprised of solar PV and

onshore wind energy capacities, leading up to around 18 percent of the installed

capacity share.

Figure (2) Installed power plant capacity of the Indian Power sector, 2017

4 ATLANTIS_India:

The Techno-economic simulation model ATLANTIS_India was developed at the

Institute of Electricity Economics and Energy Innovation, Graz University of

Technology. The model ATLANTIS_India is based on the simulation model ATLANTIS

(5), which was developed to simulate the European electricity economics, at the same

institute.

The unique feature of this model is that it combines the physical structure of the

Indian energy system, along with the economical part of the sector. This makes the

model ATLANTIS_India a one-of-its-kind model in the global energy field. The physical

model covers the transmission network, transformers, power plants and demand

center nodes over the five different power regions in India, along with Bangladesh (BA),

Bhutan (BH), Nepal (NP) and Sri Lanka (SL). The five power regions are as defined by

the Transmission System Operator in the country: East Region (ER), North East

Region (NE), North Region (NR), South Region (SR) and West Region (WR).

58.76%

7.65%

0.25%

2.06%

13.56%

17.71%

All India installed power plant capacity, 2017 in (%)

Coal Gas Diesel Nuclear Hydro Renewable


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The transmission network, nodes and the power plant data are geographically

accurate, to simulate an as-close-to-reality scenario. Transmission lines of voltage

levels 132 kV, 220 kV, 400 kV, 500 kV, 765 kV and High Voltage DC (HVDC) are

considered in the model. The economic part contains four different market models and

a business model for companies (smaller companies are segregated together for

simplicity) involved in the energy sector. The possibility to simulate the energy

economy of the fastest growing region in the world is a very interesting one, and

through ATLANTIS_India, it can be realized.

The node-specific demand distribution in the model has been done through the

assigning of weightages with respect to the total regional electricity demand, based on

population, agricultural activity and industrial activity around the region of the specific

node. The identification of the agricultural activities and industrial activities was done

by superimposing the model node GIS data with the opensource GIS maps of

agricultural lands and Special Economic Zones in the countries involved.

The model ATLANTIS_India can simulate up to four different market models, out of

which specific market model types are selected for analysis of each study, based on

the requirement. The market models are defined based on load flows and transmission

constraints. The four different market models can be explained using simple terms:

1. Copper Plate model: Without load flow calculations, and Net Transfer

Capacity restrictions, where the cheapest operational power plant in each

region is taken into consideration as the best power plant.

2. Total (Overall) Market model: With load flow calculations, and no Net Transfer

Capacity restrictions. This market model type considers the transmission lines

within each model.

3. Zonal Pricing model: The Copper Plate model, along with Net Transfer

Capacity restrictions, limiting the power exchange between each region.

4. Re-Dispatch model: Considers both load flow calculations, and Net Transfer

Capacity restrictions, giving an as-close-to-reality-as-possible approach

For the scope of this study, a large focus is on the Re-Dispatch model, as we would

like to simulate the reality as close as possible. Both the load flow distribution and the

transmission constraints, along with the Net Transfer Capacity restrictions are being

simulated for the realistic case study. The physical structure and the market model of

ATLANTIS_India is visually represented with the ATLANTIS VISU visualization tool

(5), and is as shown in the accompanying figure (3)


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Figure (3) Visualization of the physical structure in ATLANTIS_India (left) and Zonal Pricing

market model example (right)

4.1 Power plant fleet

Over 3500 power plants with total capacity of over 330 GW have been defined, with

both technical and geographical specificity in the model. Each of the power plant is

defined to feed in the power generated to the nearest defined node, possible at the

highest available transmission voltage level at the specific node. Normally, power

plants in a model are defined as close to the demand centres as possible, as this is

the case in ATLANTIS_India. However, with certain renewable energy technology

types like Hydro power, Solar PV and Wind energy, the power plants are

geographically located where the available potential is optimum. When this is the case,

a feed in line is defined to a connected nearby node already defined in the transmission

network.

The power plants in ATLANTIS_India are also defined by their technology types, fuel

used, region, owner company, and starting years. The end of use year of the power

plant, if not available, is assumed based on the assumption that the power plant

operates throughout its technical useful life time. This gives us a realistic simulation of

the real case as most power plants with long lifetimes usually end up operating more

than their economic life times mentioned in the accounting books of the owner

company. The amount of annual energy generation, along with the operational full load

hours are also to be defined for the power plant, as it gives us with an exact if not

almost exact value for the amount of generation done by the power plant during its life

time. The generation of the power plant is also distributed on a monthly basis, by

defining the generation factors, to give an estimation of the average power plant usage


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in different months in the year. This helps in giving an accurate description of the

generation by renewable resources like wind, hydro and solar, whose availability is

also dependent on the seasons in the year. A visual representation of the power plants

in the model is as shown in the Figure (4)

Figure (4) The visual representation of the power plant fleet in ATLANTIS_India

4.2 Node-specific demand model

The electricity demand distribution in the model is node- specific. This means that each

node defined in the physical model accounts for a weightage value, which distributes

the overall electricity demand and the additional demand of the specific region

accordingly based on several parameters. In the case of ATLANTIS_India, the demand

distribution is carefully done after considering the concentration of industrial, residential

and agricultural areas in the country. The three areas are targeted as they form almost

80 percent of the overall electricity demand in the country. A visual representation to

identify the concentration of these areas and their specific nodes are as shown in the

figure (5)


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Figure (5) (Left) Visual representation of the methodology followed to distribute electricity

demand (right) identification of agricultural and industrial land use in the region ER as example

Demand patterns can be immensely complicated, in the case of such a large and

complex electricity system like India. These demand patterns can vary with each

region, considering the economic growth and population densities in these regions.

Higher economic development would generally mean an increase in the intermediate

and peak load region of the load duration curve, and a higher population would mean

a general increase in the base and intermediate load region of the load duration curve.

Additional demand increases like due to electro mobility (6) and other unprecedented

causes of change in demand should also be considered, as they play a significant role

in the development of the demand pattern.

The hourly demand throughout the region is to be distributed at each node, to calculate

the load flow to and from the region. However, the important fact is that the type of

demand at each node has to be classified before distributing a certain weightage at

the node. The different demand sectors that can be classified in India include Industrial,

Agricultural, Residential, Services and Commercial. Of course, the industrial and

residential loads compromise the majority share of the electricity demand very similar

to most of the economically developing countries. However, it is to be noted that

Agriculture also occupies a major share along with the industrial and residential

sectors.

Therefore, these three demand sectors have to be classified, and then used for the

calculation of the weightage of the demand distribution at each node in the region.


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The several agricultural, industrial and residential regions in India are identified with

the help of GIS maps, and these three maps are overlaid to see the influence of each

demand sector at each geographical region. These ‘influences’ are quantified

subsequently, and the weightage at each node for the demand distribution is eventually

calculated.

The following summarizes the demand distribution methodology, and gives a clear

bird’s eye view explanation of the step by step process:

1. Identification of population intensive nodes based on general population

census data

2. Classification of Special Economic Zones and agricultural land with GIS

maps

3. Assigning the specific 40% (Industries) 30% (residential) and 30%

(agricultural) weightage classification at the node

4. Final demand distribution weightage at the particular node

5 Scenario definition

The base scenario for the Indian sub-continent was derived from the India Energy

Outlook, world Energy Outlook 2015, a report published by the International Energy

Agency. Scenario definition in ATLANTIS includes defining the overall increase in

electricity consumption, change in fuel prices, projecting additional installations of a

specific power plant type, defining the economic parameters like depreciation rates,

interest rates, inflation rates and many more specific data inputs in the model, All the

required information for defining the scenario was taken from the IEO, and a

representation of such a scenario can be seen in the figure (6) below.

Figure (6) definition of a base scenario with the NPS (IEA, 2015, (3)) as reference for India


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In the business as usual case, no new power plants are built, only the lifetimes of the

existing power plants and the automatically added gas power plants are to be

considered. This would mean that there are no specific changes to the power plant

fleet.

However, simulating the base scenario would only give you results with only the

Business-As-Usual case. Hence definition of further various scenarios becomes

important. With the energy transition goals, sustainability and long-term economic

goals in mind, four different scenarios were thought of. These scenarios were designed

based on the extent of liberalization of the power sector, and the extent of renewable

transition in mind. A visual representation of the scenarios comparing their situations

with each other can be seen in the figure (7)

Figure (7) possible Scenario definitions for India for the target year 2050

However, in the scope of this study, for the sake of simplicity and validation, only the

BAU case has been simulated and analysed.

6 Results:

The BAU scenario defined was simulated using ATLANTIS_India to validate and check

the load flows in the transmission network of the Indian subcontinent, in the scope of

this study. This scenario was simulated until the year 2050, and an overall conclusion

is taken from the resulting simulations.

The load flow in the Indian electricity system in the year 2050 is as shown in the

accompanying figure (8)


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Figure (8) Load flows in the system, 2050, overall market model

It can be observed that there are a few major bottlenecks in the transmission system,

especially in the cross-border transmission lines, and in some areas with limited power

plant capacity (north east region). Majority of the load flows are towards the NR region,

as it becomes the biggest importing region in 2050. The transmission network of the

BA region provides a bypass for the congested load flows from NE to ER, thus

alleviating some of the majorly loaded transmission lines in the area. The regions NP

and BH provide cheap electricity from Hydro power plant capacity, to the NR, ER and

NE regions.

7 Conclusions:

From the scenario simulations, several observations have been made and have been

studied carefully. In a nutshell, it can be agreed that there is a high requirement for a

techno economic model to strategize the electricity transition in India in a much more

sustainable way. ATLANTIS_India provides a great platform to achieve such scenario

simulations, and gives insights in to the technical, economic and business aspects of

such a transition.


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Observations of load flows and the loading of transmission lines gives us an overall

picture about the bottle-necks in the large Indian transmission network, and also

explains the Net Transfer Capacity situation. From the resulting load flows, it is

observed that most of the cross-border lines between the power regions are heavily

loaded, thus creating transmission bottlenecks in the system. This has to be carefully

considered, and the cross-border transmission situation has to be considerably

improved.

The regions NR and NE are observed to be importing large quantities of electricity from

the NP and BH regions. As the Net Transfer Capacity defines the limit of the total

amount of power transfer between two regions, thus for a sustainable renewable power

system, the NTCs between these regions also have to be improved.

The market models provide us an overview of the electricity pricing, thus allowing us

to optimize the power generating fleet in specific regions, while the Business model

gives us a representation of the required investments and company balance sheets for

further analysis.

Also, better scenarios (as discussed) have to be built up and analysed to have a

complete understanding of the system behaviour, and to develop a suitable strategy

for the future of the Indian Electricity system.

8 References:

(1) Power Grid Corporation India Limited (PGCIL), Annual report, Overview, 2016

(2) Executive Summary, August 2017, Central Electricity Authority, Ministry of power,

Government of India

(3) India energy outlook , World Energy Outlook Special Report, International Energy Agency,

2015

(4) Panagriya, A., ‘India in the 1980s and 1990s: A Triumph of Reforms’, IMF working paper,

March 2004

(5) U. Bachhiesl, G. Nischler, H. Stigler, ‘Techno economic modelling of the European

electricity sector’, Central European Journal of Operations Research (CEJOR)

(6) ‘An analysis on Variable Renewable Energy and the importance of Hybrid systems in India’

, Bhat, K et.al, 15th IAEE European Conference, 2017, Vienna

model based analysis of the indian electricity …...indian energy system, along with the economical...

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